Forecasting Volatility of the U.S. Oil Market

46 Pages Posted: 17 Nov 2015

See all articles by Erik Haugom

Erik Haugom

Lillehammer University College; Norwegian University of Science and Technology (NTNU)

Henrik Langeland

Norwegian University of Science and Technology (NTNU)

Peter Molnár

University of Stavanger

Sjur Westgaard

Norwegian University of Science and Technology (NTNU) - Department of Industrial Economics and Technology

Date Written: January 29, 2014

Abstract

We examine the information content of the CBOE Crude Oil Volatility Index (OVX) when forecasting realized volatility in the WTI futures market. Additionally, we study whether other market variables, such as volume, open interest, daily returns, bid-ask spread and the slope of the futures curve, contains predictive power beyond what is embedded in the implied volatility. In out-of-sample forecasting we find that econometric models based on realized volatility can be improved by including implied volatility and other variables. Our results show that including implied volatility significantly improves daily and weekly volatility forecasts, while including other market variables significantly improves daily, weekly and monthly volatility forecasts.

Keywords: oil prices, realized volatility, implied volatility, volatility forecasting

JEL Classification: G14, G13, Q47, L94

Suggested Citation

Haugom, Erik and Langeland, Henrik and Molnár, Peter and Westgaard, Sjur, Forecasting Volatility of the U.S. Oil Market (January 29, 2014). Available at SSRN: https://ssrn.com/abstract=2691391 or http://dx.doi.org/10.2139/ssrn.2691391

Erik Haugom

Lillehammer University College ( email )

Lillehammer, 2624
Norway

Norwegian University of Science and Technology (NTNU) ( email )

Trondheim NO-7491
Norway

Henrik Langeland

Norwegian University of Science and Technology (NTNU) ( email )

Trondheim NO-7491
Norway

Peter Molnár (Contact Author)

University of Stavanger ( email )

UiS Business School
Stavanger, 4036
Norway

Sjur Westgaard

Norwegian University of Science and Technology (NTNU) - Department of Industrial Economics and Technology ( email )

NO-7491 Trondheim
Norway

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